870 citations · 2.4k across the 62 of their papers we have counts for
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The Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion)
Shuo Wang, Chen Qin, Chengyan Wang +12
The quality of cardiac magnetic resonance (CMR) imaging is susceptible to respiratory motion artifacts. The model robustness of automated segmentation techniques in face of real-wo…
Improved post-hoc probability calibration for out-of-domain MRI segmentation
Cheng Ouyang, Shuo Wang, Chen Chen +4
Probability calibration for deep models is highly desirable in safety-critical applications such as medical imaging. It makes output probabilities of deep networks interpretable, b…
Mesh-based 3D Motion Tracking in Cardiac MRI using Deep Learning
Qingjie Meng, Wenjia Bai, Tianrui Liu +2
3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and diagnosis of cardiovascular diseases. Most of the pre…
Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images
Berke Doga Basaran, Mengyun Qiao, Paul M. Matthews +1
Understanding the intensity characteristics of brain lesions is key for defining image-based biomarkers in neurological studies and for predicting disease burden and outcome. In th…
Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data
Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu +6
Cardiovascular disease, the leading cause of death globally, is an age-related disease. Understanding the morphological and functional changes of the heart during ageing is a key s…
MulViMotion: Shape-aware 3D Myocardial Motion Tracking from Multi-View Cardiac MRI
Qingjie Meng, Chen Qin, Wenjia Bai +4
Recovering the 3D motion of the heart from cine cardiac magnetic resonance (CMR) imaging enables the assessment of regional myocardial function and is important for understanding a…
MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation
Chen Chen, Zeju Li, Cheng Ouyang +3
Convolutional neural networks (CNNs) have achieved remarkable segmentation accuracy on benchmark datasets where training and test sets are from the same domain, yet their performan…
Generative Myocardial Motion Tracking via Latent Space Exploration with Biomechanics-informed Prior
Chen Qin, Shuo Wang, Chen Chen +2
Myocardial motion and deformation are rich descriptors that characterize cardiac function. Image registration, as the most commonly used technique for myocardial motion tracking, i…
Suggestive Annotation of Brain MR Images with Gradient-guided Sampling
Chengliang Dai, Shuo Wang, Yuanhan Mo +3
Machine learning has been widely adopted for medical image analysis in recent years given its promising performance in image segmentation and classification tasks. The success of m…
Memory-efficient Segmentation of High-resolution Volumetric MicroCT Images
Yuan Wang, Laura Blackie, Irene Miguel-Aliaga +1
In recent years, 3D convolutional neural networks have become the dominant approach for volumetric medical image segmentation. However, compared to their 2D counterparts, 3D networ…